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App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 2

Crossmodal remote sensing semantic segmentation based on Heterogeneous graph and mamba

Ye Zhiwei1,2
Feng Qingyang1,2
Liu Mingming1,2
Wang Yuan3
Gao Rong1,2
Yan Lingyu1,2
1. School of Computer Science, Hubei University of Technology, Wuhan 430068, China
2. Hubei Provincial Key Laboratory of Green Intelligent Computing Power Network, Hubei University of Technology, Wuhan 430068, China
3. Geospatial and Natural Resources Big Data Center of Qinghai Province, Xining 810001, China
DOI: 10.19734/j.issn.1001-3695.2025.05.0225

Abstract

To address the significant crossmodal feature heterogeneity and inefficient deep semantic interaction in semantic segmentation of visible remote sensing images, this study proposes a Crossmodal Heterogeneous Graph-guided Mamba Network (CHGMNet) . The method designs a Crossmodal Heterogeneous Feature Alignment Module (CHFAM) , which constructs learnable feature similarity metrics via heterogeneous graph convolution to adaptively align spectral and geometric features within a shared semantic space, effectively alleviating dimensional mismatches across modalities. Meanwhile, it introduces a novel Multi-Path Fusion Mamba Module (MPFM) that captures multi-level fused features through a linear-complexity state space model. By integrating a multi-path adaptive architecture, the module significantly improves computational efficiency while maintaining global context modeling capability. Experimental results on two large-scale high-resolution remote sensing datasets, Vaihingen and Potsdam, demonstrate that CHGMNet significantly outperforms existing mainstream methods in mIoU, mF1, and OA metrics, validating its superiority in crossmodal remote sensing interpretation tasks.

Foundation Support

国家自然科学基金资助项目(U23A20318,62376089,62472149)
湖北省高等学校优秀中青年科技创新团队计划项目(T2023006)
湖北省科技计划立项项目(2023BEB024)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.05.0225
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 2

Publish History

[2025-11-03] Accepted Paper

Cite This Article

叶志伟, 冯青阳, 刘明明, 等. 基于异质图和Mamba的跨模态遥感语义分割 [J]. 计算机应用研究, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0225. (Ye Zhiwei, Feng Qingyang, Liu Mingming, et al. Crossmodal remote sensing semantic segmentation based on Heterogeneous graph and mamba [J]. Application Research of Computers, 2026, 43 (2). (2025-11-04). https://doi.org/10.19734/j.issn.1001-3695.2025.05.0225. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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